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A Multi-Channel Active Noise Control System Using Deep Learning-Based Method to Estimate Secondary Path and Normalized-Clustered Control Strategy for Vehicle Interior Engine Noise

SSRN

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SSRN 2024年

作者： Cheng, Can Liu, Zhien Chen, Wan Li, Xiaolong Lu, Chihua Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory Foshan528200 China

Although the multi-channel active noise control (ANC) system based on the traditional clustered control strategy solves the problems of high algorithm complexity and fragile stability, the step size setting of each local controller relies on the trial-and-error method, which makes it difficult to trade-off the convergence speed and the steady-state error of the algorithm, and the secondary path estimation is susceptible to the interference of the dynamic environment. To solve the above problems, this study proposes an efficient multi-channel ANC system, which accurately estimates the secondary paths based on the deep learning prediction model and adopts a normalized-clustered control strategy to normalize the step size of the two-channel FxLMS algorithm of each local controller, which balances the system convergence speed and the steady-state error. A series of real-vehicle ANC experiments are conducted. The results show that under stationary conditions, the proposed control strategy control converges quickly and has better noise reduction performance than the traditional clustered control strategy. Under non-stationary conditions, after normalizing the step size of the local controller, the proposed control strategy can better balance the steady-state error and the convergence speed of the control strategy and improve the noise reduction tracking ability. Finally, it is verified that the proposed deep learning method can accurately estimate the real secondary path after changes and ensure the noise reduction performance of the proposed control strategy. © 2024, The Authors. All rights reserved.

关键词： Vehicles

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Multi-Response Optimisation of Automotive Door Using Grey Relational Analysis with Entropy Weights

Research Square

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Research Square 2021年

作者： Chen, Hao Lu, Chihua Liu, Zhien Shen, Cunrui Sun, Menglei Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory Foshan528200 China Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China

Tail-welded blanks (TWBs) are widely used in automotive bodies to improve structural performance and reduce weight. The stiffness and modal lightweight design optimisation of TWBs for automotive doors was performed in this study. The finite element model was validated through physical experiments. An L27 (312) Taguchi orthogonal array was used to collect the sample points. The multi-objective optimisation problem was transformed into a single-objective optimisation problem based on the grey relational degree. The optimal combination of structural design parameters was obtained for a tail-welded door using the proposed method;the weight of the door structure was reduced by 2.83 kg. The proposed optimisation method has fewer iterations and a lower computational cost, enabling the design of lightweight TWBs. © 2021, CC BY.

关键词： Multiobjective optimization

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An Optimal Sensor Layout Method Based on Maximum Noise Reduction Estimation for Active Road Noise Control

SSRN

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SSRN 2024年

作者： Cheng, Can Liu, Zhien Li, Xiaolong Chen, Wan Lu, Chihua Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory Foshan528200 China

Active noise control (ANC) is an effective method to suppress vehicle road noise. The rapid selection of the reference sensor set and rational selection of its layout position are crucial for determining the vibration noise transmission paths with high contributions, which determines the noise reduction performance of the active road noise control (ARNC) system. The reference sensor set selected by the conventional multiple coherence function (MCOH) method does not always ensure maximum noise reduction and matrix singularity problems in the FIM-based extension method. To alleviate this problem, this paper proposes the FIM-OANR method based on the maximum overall level of theoretical noise reduction (OANR) over the target control frequency range of the control area and the fisher information matrix (FIM) to select a set of reference sensors and determine their positions. A causally constrained wiener filter estimates the theoretical maximum noise reduction for each control area, to ensure that the reference sensor set is selected with the optimal noise reduction performance. Besides, the modified expansion method for selecting a reference sensor set to avoid matrix singular in the FIM, and thus make this method more universally applicable. Numerical simulations are performed to analyze and evaluate the noise reduction performance and efficiency of the FIM-OANR method under different conditions. In addition, a series of real vehicle ANC experiments are conducted. The results show that the proposed method has an obvious advantage in noise reduction performance, it even has 2 dBA more noise reduction in each target area than the FIM-MCOH method, and only four reference sensors are needed to achieve 6.1 dBA noise reduction in ARNC. This fully confirms the effectiveness of the proposed method in real vehicle applications. © 2024, The Authors. All rights reserved.

关键词： Numerical methods

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Preparation of B4C-ZrB2-SiC ternary eutectic composites by arc melting and their properties

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Materials Research Innovations 2015年 19卷 26-29页

作者： Tu, R. Li, N. Li, Q.Z. Zhang, S. Goto, T. Zhang, L.M. State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Wuhan430070 China Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of Technology Wuhan430070 China Institute for Materials Research Tohoku University Sendai980-8577 Japan

B4C-ZrB2-SiC composites were synthesised by arc melting in Ar atmosphere using B4C, ZrB2 and β-SiC powders as starting materials. The ternary eutectic composition of 40B4C-20ZrB2-40SiC (mol-%) was first identified and a lamellar eutectic texture was observed. SiC and ZrB2 grains about 1 μm in thickness were uniformly dispersed in B4C matrix of B4C-ZrB2-SiC eutectic composite. B4C (003) and ZrB2 (100) planes were perpendicular to the growth direction. The Vickers hardness of B4C-ZrB2-SiC ternary eutectic composite was 30-34 GPa. The fracture toughness of B4C-ZrB2-SiC composite increased with the decrease of B4C content and the rise of ZrB2 content. © 2015 W. S. Maney & Son Ltd.

关键词： Silicon carbide

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Nox Emission Prediction of Heavy-Duty Diesel Vehicles Based on Bo-Gru Algorithm

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SSRN 2023年

作者： Wang, Zhihong Luo, Kangwei Yu, Hongsen Feng, Kai Ding, Hang School of Automotive Engineering Wuhan University of Technology Hubei Wuhan430070 China Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Hubei Wuhan430070 China

In accordance with the requirements of GB17691-2018 "Emission Standards and Measurement Methods for Heavy-Duty Vehicles (China VI Stage)", this study conducted actual on-road emission tests on a specific N2 heavy-duty diesel vehicle using onboard portable emission measurement systems (PEMS). The collected data underwent processing steps such as data alignment and removal of invalid data, resulting in cleaned data. Based on this, the top 10 parameters with significant impact on NOx emissions were selected through gray correlation analysis, and principal component analysis was applied to reduce the dimensionality of input parameters. The data was then integrated in a time series manner and rearranged to create new operating condition data. A gated recurrent unit (GRU) neural network based on Bayesian hyperparameter optimization was established, utilizing a combination of cosine annealing and exponential learning rate adjustment strategy during training. The root mean square error (RMSE) on the test set was 1.2352 (mg·s-1), and the coefficient of determination (R2) was 0.9569. This research provides a possible approach for online monitoring of NOx emissions in heavy-duty diesel vehicles. © 2023, The Authors. All rights reserved.

关键词： Principal component analysis

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A vehicle electric control unit over-the-air reprogramming system

A vehicle electric control unit over-the-air reprogramming s...

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International Conference on Connected Vehicles and Expo (ICCVE)

作者： Guoyong Shi Zhiwei Ke Fuwu Yan Jie Hu Wenjie Yin Yanhong Jin SAIC GM Wuling Automobile Co. Ltd. Liuzhou Guangxi China Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan Hubei China Technical Center Dongfeng Renault Co. LTD Wuhan Hubei China

For the purpose of aftermarket automotive ECU (Electric Control Unit) software upgrading, it is necessary to build an automotive ECU OTA(Over-The-Air) reprogramming system. To obtain a convenient electronic control unit upgrading that aftermarket consumers can achieve by themselves, the server system should be connected to 3G / 4G which is linked to a VCI (Vehicle Communication Interface) System. The VCI is also connected to OBD II, vehicle network and finally to the ECU. Accuracy and flexibility of the reprogramming file can be ensured by establishing a correspondence with the VIN code (the only identification code of a vehicle) and the reprogramming file. A reprogramming program can be developed based on the android system on the VCI and a connection with the CAN bus. The update command is sent out by smart phone. Tests made proved that the system is reliable, convenient and greatly simplifies the reprogramming process.

关键词： Decision support systems Conferences Connected vehicles

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Numerical solution for thermodynamic model of charge-discharge cycle in compressed hydrogen tank

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Energy Procedia 2019年 158卷 2145-2151页

作者： Feng Li Tianqi Yang Jinsheng Xiao Pierre Bénard Richard Chahine Hubei Key Laboratory of Advanced Technology for Automotive Components and Hubei Collaborative Innovation Center for Automotive Components Technology School of Automotive Engineering Wuhan University of Technology Hubei 430070 China Hydrogen Research Institute Université du Québec à Trois-Rivières QC G9A5H7 Canada

The safety and convenience of hydrogen storage are significant for fuel cell vehicles. Based on mass conservation equation and energy conservation equation, two thermodynamic models (single zone model and dual zone model) have been established to study the hydrogen gas temperature and tank wall temperature for compressed hydrogen storage tank. With two models, analytical solution and Euler solution for single zone (gas zone) charge-discharge cycle have been compared, Matlab/Simulink solution and Euler solution for dual zone (gas zone, wall zone) charge-discharge cycle have been compared. Three charge-discharge cycle cases (Case 1, constant inflow temperature; Case 2, variable inflow temperature; Case 3, constant inflow temperature variable outflow temperature) and two compressed hydrogen tanks (Type III 25L, Type IV 99L) charge-discharge cycle are studied by Euler method. Results show Euler method can well predict hydrogen temperature and tank wall temperature.

关键词： compressed hydrogen storage charge-discharge cycle numerical solution Euler method safety

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Detection of Emergency Braking Intention Based on Pedal-Switching Process

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IEEE Access 2024年

作者： Xu, Chuyong Xu, Lin Han, Chengleng Li, Shicheng Feng, Zhenyang Wuhan University of Technology Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan430070 China Wuhan City Polytechnic School of Automotive Technology and Service Wuhan430070 China

The driver's reaction time and the brake actuator response time during emergency braking play a crucial role in braking distance. Detecting the driver's braking intention and reducing actuator reaction time can enhance the safety advantages of the intelligent braking system. This study introduces a braking intent recognition method based on detecting the driver's transition between the accelerator and brake pedals. This approach can seamlessly integrate with the brake-by-wire (BBW) system, leveraging the advantages of complete decoupling between the brake pedal and the actuator. This study initially examines the braking process and then presents the proposed braking intent recognition technique. The driver's pedal-switching action is characterized by a time-varying vector, which is integrated into the detection module. Various feature extraction methods are introduced to analyze the accelerator release speed and time-varying vectors under emergency and normal braking scenarios separately. Leveraging these features, a predictive model is developed using machine learning methods. The effectiveness of the proposed detection system and predictive model is validated through pseudo-online simulations. Results demonstrate a high recognition accuracy of 96.2% for the emergency braking intention detection system. Moreover, the proposed method shows the capability to predict braking intentions about 36 ms prior to the brake pedal being pressed during emergency braking and about 589 ms in advance during normal braking. The proposed approach has the potential to reduce braking distances significantly, serving as a valuable enhancement to Active Driving Assistance Systems (ADAS) for improved braking safety. © 2013 IEEE.

关键词： Brakes

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Estimation of filling time for compressed hydrogen refueling

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Energy Procedia 2019年 158卷 1897-1903页

作者： Xin Zhou Tianqi Yang Jinsheng Xiao Pierre Bénard Richard Chahine Hubei Key Laboratory of Advanced Technology for Automotive Components and Hubei Collaborative Innovation Center for Automotive Components Technology School of Automotive Engineering Wuhan University of Technology Hubei 430070 China Hydrogen Research Institute Université du Québec à Trois-Rivières QC G9A5H7 Canada

In order to facilitate the application of hydrogen energy and ensure its safety, the compressed hydrogen storage tank on board needs to be full of hydrogen gas within 3 minutes. Therefore, to meet this requirement, the effects of refueling parameters on the filling time need to be investigated urgently. For the purpose of solving this issue, a novel analytical solution of filling time is obtained from a lumped parameter model in this paper. According to the equation of state for real gas and dimensionless numbers Nu and Re, the function relationships between the filling time and the refueling parameters are presented. These parameters include initial temperature, initial pressure, inflow temperature, final temperature and final pressure. These equations are used to fit the reference data, the results of fitting show good agreement. Then, the values of fitting parameters are further utilized so as to verify the validity of these formulas. We believe this study can contribute to control the hydrogen filling time and ensure the safety during fast filling process.

关键词： compressed hydrogen storage hydrogen refueling filling time thermodynamics safety

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Influences of key process parameters on orbital forging of thin-walled smartphone shell frame of aluminum alloy

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Procedia Manufacturing 2020年 50卷 303-306页

作者： Binting Gu Wuhao Zhuang Xinghui Han School of Materials Science and Engineering Wuhan University of Technology Wuhan 430070 China Hubei Key Laboratory of Advanced Technology of Automotive Components Wuhan University of Technology Wuhan 430070 China

Smartphone shell frame is a thin-walled component, which is quite difficult to be fabricated by integral die forging process because of narrow die cavity and high forging load. In this paper, an orbital forging process is proposed to forge the thin-walled smartphone shell frame. Firstly, a FE model on orbital forging of thin-walled smartphone shell frame is developed under Deform-3D platform. By using this model, the influences of initial temperature of workpiece T , tilt angle of swing die γ and feed moment per rotation λ on temperature distribution, equivalent strain distribution and forging load are comprehensively discussed. The results show that final temperature of workpiece compared with initial temperature of workpiece T can be improved with decreasing initial temperature of workpiece T , increasing tilt angle of swing die γ and increasing feed moment per rotation λ . Equivalent strain is positively correlated with tilt angle of swing die γ , negatively correlated with feed moment per rotation λ and almost unaffected by initial temperature of workpiece T . Moreover, forging load can be obviously reduced by increasing initial temperature of workpiece T , increasing tilt angle of swing die γ and decreasing feed moment per rotation λ .

关键词： Thin-walled Smartphone shell frame Orbital forging key process parameters Aluminum alloy

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